AIMC Topic: White
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Using a Multilingual AI Care Agent to Reduce Disparities in Colorectal Cancer Screening for Higher Fecal Immunochemical Test Adoption Among Spanish-Speaking Patients: Retrospective Analysis.
Journal of medical Internet research
Jun 25, 2025
BACKGROUND: Colorectal cancer (CRC) screening rates remain disproportionately low among Hispanic and Latino populations compared to non-Hispanic White populations. While artificial intelligence (AI) shows promise in health care delivery, concerns exi...
Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.
Scientific reports
Feb 18, 2025
This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from African American adults (18-85) in Southeastern Virginia (2016-2020), we found Mood Affective Disorders we...
A Comparison of Prostate Cancer Screening Information Quality on Standard and Advanced Versions of ChatGPT, Google Gemini, and Microsoft Copilot: A Cross-Sectional Study.
American journal of health promotion : AJHP
Jan 24, 2025
PurposeArtificially Intelligent (AI) chatbots have the potential to produce information to support shared prostate cancer (PrCA) decision-making. Therefore, our purpose was to evaluate and compare the accuracy, completeness, readability, and credibil...
Evaluating machine learning model bias and racial disparities in non-small cell lung cancer using SEER registry data.
Health care management science
Nov 4, 2024
BACKGROUND: Despite decades of pursuing health equity, racial and ethnic disparities persist in healthcare in America. For cancer specifically, one of the leading observed disparities is worse mortality among non-Hispanic Black patients compared to n...
Racial and Ethnic Disparities in Predictive Accuracy of Machine Learning Algorithms Developed Using a National Database for 30-Day Complications Following Total Joint Arthroplasty.
The Journal of arthroplasty
Oct 20, 2024
BACKGROUND: While predictive capabilities of machine learning (ML) algorithms for hip and knee total joint arthroplasty (TJA) have been demonstrated in previous studies, their performance in racial and ethnic minority patients has not been investigat...
Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data.
JMIR public health and surveillance
Sep 26, 2024
BACKGROUND: Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these obse...
Optimal Pair Matching Combined with Machine Learning Predicts a Significant Reduction in Myocardial Infarction Risk in African Americans Following Omega-3 Fatty Acid Supplementation.
Nutrients
Sep 2, 2024
Conflicting clinical trial results on omega-3 highly unsaturated fatty acids (n-3 HUFA) have prompted uncertainty about their cardioprotective effects. While the VITAL trial found no overall cardiovascular benefit from n-3 HUFA supplementation, its s...
Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Aug 14, 2024
INTRODUCTION: The incidence of Alzheimer's disease (AD) and obesity rise concomitantly. This study examined whether factors affecting metabolism, race/ethnicity, and sex are associated with AD development.
Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model.
BMC pregnancy and childbirth
Jun 22, 2024
BACKGROUND: Differential exposure to chronic stressors by race/ethnicity may help explain Black-White inequalities in rates of preterm birth. However, researchers have not investigated the cumulative, interactive, and population-specific nature of ch...
Assessing fairness in machine learning models: A study of racial bias using matched counterparts in mortality prediction for patients with chronic diseases.
Journal of biomedical informatics
Jun 13, 2024
OBJECTIVE: Existing approaches to fairness evaluation often overlook systematic differences in the social determinants of health, like demographics and socioeconomics, among comparison groups, potentially leading to inaccurate or even contradictory c...
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